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Airspace congestion smoothing by stochastic optimization

  • Issues in Evolutionary Optimization
  • Conference paper
  • First Online:
Evolutionary Programming VI (EP 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1213))

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Abstract

This paper addresses the general time-route assignment problem: One considers an air transportation network and a fleet of aircraft with their associated route and slot of departure. For each flight a set of alternative routes and a set of possible slots of departure are defined. One must find “optimal” route and slot allocation for each aircraft in a way that significantly reduces the peak of workload in the most congested sectors and in the most congested airports, during one day of traffic.

A state of the art of the existing methods shows that this problem is usually partially treated and the whole problem remains unsolved due to the complexity induced. Genetic algorithms are then presented and adapted in a way to solve large instance of the problem.

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Author information

Authors and Affiliations

  1. Centre d'Etude de la Navigation Aérienne, 9, rue Champagne, 91200, Athis-Mons, France

    Daniel Delahaye

  2. Massachusetts Institute of Technology, 02139, Cambridge, MA, USA

    Amedeo R. Odoni

Authors
  1. Daniel Delahaye
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  2. Amedeo R. Odoni
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Editor information

Peter J. Angeline Robert G. Reynolds John R. McDonnell Russ Eberhart

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© 1997 Springer-Verlag Berlin Heidelberg

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Delahaye, D., Odoni, A.R. (1997). Airspace congestion smoothing by stochastic optimization. In: Angeline, P.J., Reynolds, R.G., McDonnell, J.R., Eberhart, R. (eds) Evolutionary Programming VI. EP 1997. Lecture Notes in Computer Science, vol 1213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0014809

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  • DOI: https://doi.org/10.1007/BFb0014809

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62788-3

  • Online ISBN: 978-3-540-68518-0

  • eBook Packages: Springer Book Archive

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